The primary goal of a proteomic analysis is to be able to systematically identify and quantify the majority of proteins expressed in a cell or tissue. The conventional approach for conducting proteome-wide studies is two-dimensional polyacrylamide gel electrophoresis (2D-PAGE), where a large number of proteins can be separated on the basis of their isoelectric point and molecular weight. Although 2D-PAGE technology has been the chief technology for proteomic analysis to date, it has recognized limitations, such as a bias toward the most abundant proteins and dynamic range and protein solubility issues that complicate the detection and separation of low-abundance and hydrophobic proteins. In recent years, a number of researchers have focused on improving proteomic analyses via the development of shotgun proteomic methods. These methods identify and quantify proteins that have not been separated prior to digestion. The basis of this approach is to perform a batch digestion of an unseparated protein mixture, to separate the resulting peptides by one or more dimensions of liquid chromatography, and to identify the proteins from which the peptides derive by mass spectrometry analysis.
Two mass spectrometry approaches for shotgun proteomic analysis have been reported. First is the use of tandem mass spectrometry to generate fragmentation data that can be used by search engines to identify the protein origin of the peptides. These methods are able to detect and identify a wide variety of protein classes including those with extremes in isoelectric point, molecular weight, abundance, and hydrophobicity. However, these methods are time consuming and produce very large data sets, as they require the generation of a fragmentation spectrum for each peptide in a mixture that contains thousands of components. A second approach is the use of accurate mass measurement to identify proteins. If the molecular masses of the peptides from a batch digest are measured with high enough mass measurement accuracy (MMA), a reasonable fraction of their masses can uniquely identify them by comparison to a list of masses for all of the possible proteolytic peptides predicted from an in silico digest of the genome. Other experimental information can be used to increase the fraction of identified peptides, for example, HPLC retention time. Methods that combine MMA with the MS/MS capabilities have also been reported.
Thus, there is a need in the industry to overcome these deficiencies.